The recent development of tools for studying large numbers of genes and proteins has led to a new interest in determining the structure and function of gene networks and has, for the first time, allowed a direct elucidation of the connections and logical organization of gene networks. Our understanding of the processes which structure genes into networks and determine variability of those networks has been limited by a lack of theoretical work which explicitly takes network structure into account. Gene networks are important because they contain the interactions which produce complex phenotypes, and perturbations of the genes in these networks may cause disorders in their bearers or increased virulence in pathogens. Recent theoretical work has attempted to classify gene and protein networks, associate network topology with evolutionary rates, and associate network topology with the magnitude of phenotypic defects. These studies do not provide causal models of the evolution of network function, nor do they take into account features and constraints of particular gene networks. The first aim of this proposal is to model two key features of gene networks: Robustness to mutational change and accumulation of genetic variance. These related features are important in determining which genes in a network will be most likely to vary and to be associated with deviant phenotypes. The second aim is to apply these models to the specific case of the chemotaxis network of bacteria. This network is well characterized and DNA databases already contain the information to test the predictions made from aim 1. The third aim is to refine models of the chemotaxis network based on the outcome of aim 2, and to develop general methods for using comparative genomic data to refine mechanistic models of gene networks. This work will increase our understanding of the forces that structure gene networks and our ability to predict which genes are most likely to cause disease. [unreadable] [unreadable]